Touchless virtual card payment automation

ABSTRACT

A system to process virtual credit card (VCC) payments automatically is provided. Electronic delivery of VCC payment information may be transferred as electronic data representing a VCC payment to the seller (e.g., an email). Data exchange methods for VCC payments include application programming interfaces (APIs), email, files, etc. Secure processing is provided via an environment that meets rigorous security standards (e.g., Payment Card Industry (PCI) data security standards). Credentials of the sending entity establish the context that allows the system to associate the data received with the correct buyer and seller. Authentication may be provided within the context of the data transferred. Authentication may also use the sender&#39;s email address to validate the sender using a digital signature of the email contents. The system may combine digital signature validation of an email with a validation of a sending entity using the DomainKeys Identified Mail (DKIM) email authentication protocol.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.16/411,734 (U.S. Publication No. US-2020-0265415-A1) filed on May 14,2019, entitled, “Touchless Virtual Card Payment Automation”, and whichclaims the benefit of Indian Application No. 201941006157, filed Feb.15, 2019. This application is incorporated herein by reference in itsentirety to the extent consistent with the present application.

BACKGROUND

Payment methods for transactions in commerce may be structured asBusiness-to-Business commerce (commonly referenced with the acronym“B2B”). Some purchases of goods for resale are from a manufacturer,other purchases of goods may be for raw materials that are made intogoods for sale. Providers and purchasers utilize several methods tomanage cash flow with respect to purchases and payments (e.g., a paymentprocessing system). B2B commerce differs from Business-to-Consumercommerce (commonly referenced with the acronym “B2C”) where consumerspurchase from a provider, typically for consumption rather than resale.B2C transactions occur in retail stores or through on-line shopping. Inmost cases, B2C commerce involves a direct payment from the consumer tothe provider at the time goods or services are delivered. Direct paymentmay include a cash transaction or using a credit card from a recognizedconsumer credit card provider (who provides funds immediately to theprovider and assumes a risk in payment on the part of the consumer).

In contrast to B2C where payment may be made concurrently with purchase,B2B commerce transactions often include a relationship that isestablished between the two businesses. For example, net 15 means thatpayment will be made within 15 days. In some cases, providers may have acredit management department to verify a buyer's organization contactinformation, credit worthiness, necessary licensing credentials, andother information used to establish the business relationship. Creditmanagement departments may establish terms of payment based on therelationship which will likely differ for different relationships. Insome cases, the terms may indicate that the buying entity (purchaser)pays cash (or otherwise settles the account e.g., wire transfer offunds) upon delivery of goods. In other cases, a credit limit andpayment terms may be established to allow the purchaser to acquire goodswithout immediate payment as long as the established credit limit is notexceeded (e.g., remains within a limit threshold). This type of creditrelationship differs from that of the consumer credit card above, atleast in that there is no third party (i.e., consumer credit cardprovider) to assume a risk of non-payment on the part of the purchaser.

In B2B transactions, payment terms established by a provider in therelationship may introduce or allow for a delay in payment to the sellerfrom the buyer. When payment is received by the provider, a payment inthe form of a check may introduce an additional delay or uncertainty inthe delivery of funds to the provider. Further, checks must be depositedin the provider's bank, the provider's bank requests a transfer of moneyfrom the purchaser's bank account, and the provider's bank updates theprovider's account balance to reflect the payment. These additionalsteps may take several days to complete or may even result in thepurchaser's bank rejecting the request (e.g., due to insufficient fundsor other reasons).

To make the receipt of payments more efficient and less prone to theuncertainty of receiving funds, many providers participating in B2Btransactions desire utilizing methods and systems to accept electronicpayments. One existing technique utilized by providers to obtain paymentincludes processing of electronic checks. An Automated Clearing House(ACH) has been used by providers to shorten the time it takes for aprovider to receive funds from a check. ACH transactions, however, asdiscussed above maintain an element of uncertainty to the provider withrespect to actual receipt of funds. Further, data managed to facilitateACH transactions may also introduce additional burdens on each of theprovider and purchaser to ensure each transaction is processedsuccessfully and securely.

There is a need to address the above issues and provide more efficientprocessing of payments. To address this need, disclosed system andmethods provide for a touchless virtual card payment process that may beused in different types of supplier/provider scenarios.

BRIEF DESCRIPTION OF THE DRAWINGS

The present disclosure may be better understood from the followingdetailed description when read with the accompanying Figures. It isemphasized that, in accordance with standard practice in the industry,various features are not drawn to scale. In fact, the dimensions orlocations of functional attributes may be relocated or combined based ondesign, security, performance, or other factors known in the art ofcomputer systems. Further, order of processing may be altered for somefunctions, both internally and with respect to each other. That is, somefunctions may not require serial processing and therefore may beperformed in an order different than shown or possibly in parallel witheach other. For a detailed description of various examples, referencewill now be made to the accompanying drawings, in which:

FIG. 1 is an example block diagram illustrating a transaction flow for aprovider and recipient of services/goods (purchaser) ecosystem wherecredit card payments are made by the purchaser, according to one or moredisclosed example implementations;

FIG. 2A is a block diagram illustrating interfaces within and externalto a VCC payment receiver function including a detailed view of examplesubsystems that may be utilized by the VCC payment receiver, accordingto one or more disclosed example implementations;

FIG. 2B is another block diagram illustrating interfaces within andexternal to a VCC payment receiver function including a detailed view ofexample subsystems that may be utilized by the VCC payment receiver,according to one or more disclosed example implementations;

FIG. 3 is a flow diagram depicting an example method for processing of aVCC payment, according to one or more disclosed example implementations;

FIG. 4 is an example computing device, with a hardware processor, andaccessible machine-readable instructions stored on a machine-readablemedium that may be used to process a VCC payment, according to one ormore disclosed example implementations;

FIG. 5 is a flow diagram depicting at least two possible payment flows,including an automatic payment flow and an interactive (e.g., withmanual component) flow for processing of a VCC payment, according to oneor more disclosed example implementations;

FIG. 6 is an example computing device, with a hardware processor, andaccessible machine-readable instructions stored on a machine-readablemedium that may be used to execute the payment flows of FIG. 5,according to one or more disclosed example implementations;

FIG. 7 is a computer network infrastructure that may be used toimplement all or part of the disclosed VCC payment processing system,according to one or more disclosed example implementations;

FIG. 8 illustrates a computer processing device that may be used toimplement the functions, modules, processing platforms, executionplatforms, communication devices, and other example methods andprocesses of this disclosure; and

FIG. 9 is a block diagram of a credit card processing ecosystem where acardholder establishes a relationship with a card issuer to receive aphysical or virtual credit card used for performing credit card paymentsto a provider of goods or services, according to one or more disclosedexample implementations.

DETAILED DESCRIPTION

Illustrative examples of the subject matter claimed below will now bedisclosed. In the interest of clarity, not all features of an actualimplementation are described for every example provided in thisspecification. It will be appreciated that in the development of anysuch actual example, numerous implementation-specific decisions may bemade to achieve the developer's specific goals, such as compliance withsystem-related and business-related constraints, which will vary fromone implementation to another. Moreover, it will be appreciated thatsuch a development effort, even if complex and time-consuming, would bea routine undertaking for those of ordinary skill in the art having thebenefit of this disclosure.

Providers that participate in a B2B transaction may utilize electronicdata transfers to securely and efficiently receive payment for goods andservices delivered to purchasers. Disclosed techniques illustrate usesof a VCC as a method of processing B2B payments. Disclosed systemsrepresent a more secure alternative and efficient transaction process ascompared to ACH and check payments. As disclosed, VCC techniquesrepresent, at a high level, a “card-less” credit card payment. As usesof VCC type transactions become more prevalent, providers of goods andservices may recognize an improvement to the processing performed withinand across disclosed computer systems to process payments using avirtual credit card. Disclosed techniques may represent an improvementto both the computer processing and the efficiency of obtainingremittance as part of the purchase transaction.

In traditional systems that process concepts of a VCC, that processingmay be manual and inefficient. In these systems, the workflow may beginwith a VCC payment being sent to a seller in the form of an email. Theemail may contain the VCC number and other remittance data such as theamount of the payment, a breakdown of invoices mapped to amounts thepurchaser is intending to have the payment applied, and any otherinformation to be used by the seller to successfully process a paymentbased on the VCC (and other email information). An employee, at thereceiving end of the email, may then interactively transcribe data fromthe email containing the VCC remittance data into a computer system toprocess the payment. In addition to the time and effort to perform thistranscription, the employee may need to analyze how to properly processthe transaction in order to minimize the fees that the provider will becharged with respect to processing the electronic payment (e.g., feesfor utilizing third party systems). A provider processing a large numberof payments in this manner may not realize possible efficiency gainsthat are possible using VCC transactions. Specifically, if theprovider's employees are spending a significant amount of time toprocess VCC payments, then processing a large number inefficiently mayineffectively utilize resources.

Disclosed systems and techniques may enable a providing entity (e.g.,provider) to more efficiently process each individual VCC payment whilefurther reducing or eliminating any manual actions that may currently beembedded within their payment processing methodology. In one exampleimplementation, a system allows electronic delivery of VCC paymentinformation using any method of transferring electronic data to theseller. In this example, an entity sending the VCC payment data may be,for example, a purchaser (e.g., end-user or subsequent provider within asupply chain), a card issuer (e.g., creator of a VCC on behalf of thepurchaser), or any other entity transmitting VCC payment data. In thisexample, the system may accept VCC payment data from a plurality ofsources and using a plurality of different data exchange methods. Dataexchange methods in this context may be, for example, applicationprogramming interfaces (APIs) of any type, email, files, files attachedto emails, and any other method of electronic data exchange.

To facilitate the secure processing of VCC payment, the electronic datareceived by the system may be stored and processed in an environmentthat may meet very rigorous security standards such as, for example,security standards conforming to Payment Card Industry (PCI) datasecurity standards. Processing the received data in the secureenvironment may prevent the unintended disclosure of the data used toprocess VCC payment.

Disclosed systems running in the secure environment to process VCCpayments may receive VCC payment information via a method where thesending entity presents authenticatable credentials when establishing aconnection. Authenticatable credentials, in this context, refer to ausername and password, a shared secret, a security certificate, or anyother method that allows the identity of the sending entity to beauthenticated. Data exchange methods such as APIs or file transferprotocols are examples different data exchange methods that may useauthenticated connections. Using an API as a method to exchangeelectronic data, for example, generally allows explicit declaration ofcontextual information about the data exchange. This contextualinformation may be, for example, credentials supplied by the sendingentity when the communication channel is established at the time that asending entity connects to the system. The credentials of the sendingentity may establish the context that allows the system to associate thedata received with the correct purchaser and provider.

A system running in the secure environment that processes VCC paymentsmay, for example, receive VCC payment information via a method that doesnot require any authentication from the sending entity. In this case,the context of which provider and purchaser are associated with thetransaction data may be established by identifying information in thereceived data and later validating the data was sent from an authorizedentity. Receiving an email with transaction information, for example,requires no authentication by the sender. The sender, however, mayaddress the email to an email address established by the seller forreceiving virtual credit card payment transactions. The system, havingreceived the email for a provider, may use multiple methods forverifying the authenticity and origin of the email. The system may, forexample, use the sender's email address to validate the sender using adigital signature of the email contents. The system may combine thedigital signature validation of the email with a validation of thesending entity using, for example, the DomainKeys Identified Mail (DKIM)email authentication protocol to verify the mail was sent from a systemowned by the sender. Many methods may be combined to perform validationof electronic data post-receipt.

VCC payment data received may be in a form that is interpreted by amachine such that all, or part of, the received data may be transformedinto a credit card payment transaction. This type of data format may bevery similar to a computer programming language, in that the data formmay be designed to be readable by a human and a computer by eliminatingthe ambiguities of spoken languages. While this form of data may bereadable by a human, a human may not find it as easy to read as datathat is a textual representation of a spoken language (e.g. a book, amagazine, or a newspaper article). Data formats such as ExtensibleMarkup Language (XML), JavaScript Object Notation, and other datainterchange formats are examples of forms that are interpreted by acomputer.

VCC payment data received in a form that is a textual representation ofa spoken language may also be received by the system. A textual form ofa spoken language may be processed using techniques such as ArtificialIntelligence (AI) and Natural Language Processing (NLP) to transformthat data to a form that may be more easily processed by a machine. AIand NLP algorithms may be used to extract data elements from thereceived textual representation of a spoken language that is required tosuccessfully process a credit card transaction. Data extracted mayinclude any data that may be used as part of a credit card paymenttransaction. Data may include, but is not limited to, a virtual orphysical credit card number, a card expiration date, a card verificationvalue (CVV), a purchase order number, and invoice line item details. TheAI and NLP algorithms may be combined with multiple templates that maybe used to allow the AI and NLP algorithms to extract data with higherspeed and increased accuracy.

Disclosed systems may automatically process credit card paymenttransactions from electronic data received in any form. The dataextracted from the received electronic data may be validated againstcriteria that assess if there is enough data to perform a transactionsuccessfully or, if the fees assessed by the credit card processor forprocessing the transaction are below an acceptable threshold, to allowfor automatic processing. If a credit card payment transaction createdfrom the received electronic data does not meet the criteria forautomatic processing, the transaction may be held for further review andapproval (or exception processing). The further reviewing of thetransaction may optionally add additional data to the credit cardtransaction before processing. This additional data may allow thetransaction to incur lower fees by the credit card processor. Thefurther review may also allow the transaction to be processed byindicating that the system should process the credit card paymenttransaction and disregard any validation failures that prevented thecredit card payment transaction from previously processingautomatically.

Disclosed systems may periodically collect all credit card paymenttransactions recorded and communicate with the credit card processor tocomplete the transfer of funds. That is, to produce a result ofcompleting transfer of one or more buyers' credit card paymenttransactions to the provider's account. This activity may commonly bereferred to as a “transmitting a settlement batch to the processor”.Upon successfully transmitting a settlement batch to the processor, thesystem may send an electronic data transaction to the provider'sEnterprise Resource Planning (ERP) system. The ERP system, in thiscontext, is where a provider may store all records related to financialtransactions executed as part of running the provider's business. Theupdate to the ERP system may have many purposes. One common purpose inupdating the ERP system is to record the credit card payment transactionto apply the payment one or more of a purchaser's outstanding invoicebalances.

Disclosed systems may also communicate with one or more financialinstitutions, on behalf of the provider, to deposit funds from creditcard payment transactions and to receive account deposit statements. Theaccount deposit statements may be used to update the ERP system onceagain to confirm that credit card transaction payments have beenconfirmed as deposited into the provider's bank account. This activitymay be commonly referred to as “settlement reconciliation”. The systemmay also update the ERP system to reverse a payment against apurchaser's invoice. For example, if during settlement reconciliation apayment was reversed by the credit card processor at the purchaser'srequest. A credit card processor reversing a payment at a purchaser'srequest is commonly referred to as a “charge back.” A charge back mayoccur in cases where, for example, the purchase from the provider wasfraudulently executed using the purchaser's stolen credit card number oreven when the purchaser and the provider have a dispute about the termsof the transaction.

Having an understanding of the above overview, this disclosure will nowexplain a non-limiting but detailed example implementation. Otherimplementations and other variants of this example implementation arecertainly possible and will become apparent to those of skill in theart, given the benefit of this disclosure. This example implementationis explained with reference to the drawings in which like elementsmaintain their reference numbers across different figures. Note that anelement and corresponding reference number may be the same in twodifferent figures even if the element has, based on an example beingpresented, changed in state between the two different figures. That is,in a hypothetical example used for explanatory purposes, a componentitem illustrated in one figure may maintain its element number acrossdifferent figures, even if that component item has been processed andaltered in some manner by a previously discussed processing action.

Referring now to FIG. 1, shown is an example block diagram of apurchaser and provider ecosystem 100 where credit card payments are madeby a purchaser 115, in accordance with one or more disclosedimplementations. The examples described with reference to this figurewill refer to credit card payments made by VCCs, but this is notintended to limit the system to only accepting VCCs. The system mayaccept any type of payment instrument that may be used by a purchaser topay a provider for goods and services.

Ecosystem 100 is comprised of one or more purchaser system domains 105and one or more provider system domains 110. For purposes of brevity,the example will discuss a single purchaser and a single provider but isnot limited to the application of the system described to only apply toone purchaser 115 and one provider 130. Each system domain 105 and 110demonstrates the systems that may be used by each entity in conducting abusiness transaction. In this example, purchaser 115 may have anEnterprise Resource Planning (ERP) system 120 that tracks financialtransaction records as part of performing activities related to theenterprise of purchaser 115. These types of transactions may include,but are not limited to, accounts payable, accounts receivable, supplychain management, payroll, or inventory management. Purchaser 115 mayhave a business relationship with the provider 130 and, after purchasinga good or a service from provider 130, may wish to pay provider 130 forthe purchase. Purchaser 115 may contact their financial institution 125to issue a payment using a virtual credit card. The purchaser'sfinancial institution, in this context, plays the role of “issuing bank125” when the bank issues a VCC payment to be sent to systems in theprovider's system domain 110. In this context, the act of “sending acredit card payment” may include any sort of transmission of datathrough physical or electronic means.

The provider's system domain 110 may have a system dedicated toreceiving payment information such as the VCC payment receiver 135 shownin FIG. 1. Issuing bank 125 may transmit a VCC payment to VCC paymentreceiver 135 through any method of electronic data exchange. Thiselectronic data exchange may commonly occur when, for example, theissuing bank 125 transmits an email, transmits an email with anattachment, transmits a file, or performs an Application ProgrammingInterface (API) call that transfers the electronic data required for theprovider 130 to perform a credit card payment transaction by sendingcredit card transaction data to a credit card processing gateway 140.Data required to build a credit card transaction may be extracted fromthe data received from the issuing bank 125. Transforming data receivedfrom the issuing bank 125, when received via an API call, may beexecuted using a mapping method. Data transfer through an API callcommonly requires a strict interpretation agreement between the APIsender and receiver. An API call will commonly validate that datareceived is in an understandable format before allowing the data to forminto a credit card transaction.

Transforming data received from the issuing bank 125 that is, forexample, received by email, by email with one or more attachments, or asa file may require additional processing to transform the data info acredit card payment transaction. An email, an email with one or moreattachments, or a file, unlike an API call, may contain data that is atextual form of a spoken language for the purpose of a human being ableto read the email. VCC payment receiver 135 may attempt several methodsof extracting data from an email, an email with one or more attachments,or a file. One method may include matching data fields in the email,attachment, or file to data fields described in an email template. Thetemplate, in this context, describes the expected location of data in anemail, attachment, or file sent by an issuing bank 125. A single issuingbank 125 may have multiple email formats that are used, thereforemultiple templates may be used to attempt to read credit card paymenttransaction data via templates.

In some cases, an issuing bank 125 may send emails, one or moreattachments, or one or more files that do not allow a template to bereliably applied to the email, one or more attachments, or one or morefiles for data extraction purposes. In this case, an additional methodof applying artificial intelligence (AI) and natural language processing(NLP) may be used to extract data from the email, one or moreattachments, or one or more files. When using these techniques,datafields may be extracted from the email, one or more attachments, orone or more files and a credit card payment transaction may be createdfor transmission to a credit card processing gateway 140. The use ofthese techniques is for illustrative purposes only and not intended tolimit the techniques that may be used or the combination of techniquesthat may be used to extract credit card payment transaction data from anemail, one or more attachments, or one or more files.

Credit card processor gateway 140 may accept credit card paymenttransaction data and interpret the data for sending to credit cardprocessor 145. This example shows credit card processor gateway 140using a single credit card processor 145, but this is for purposes ofbrevity only. It may be common for a credit card processor gateway 140to utilize one or more credit card processors 145 for the purpose ofprocessing a wide variety of credit card payment transactions.

The provider 130 may also have an ERP system 155 in the provider'ssystem domain 110 that is updated by credit card processor gateway 140as credit card payment transactions are processed. In this context,“processing a credit card transaction” may include an initial request tocredit card processor 145 to authorize and reserve funds for atransaction. The initial authorization and reservation request may befollowed by other requests such as a settlement request where creditcard processor 145 is instructed to transfer funds from card issuingbank 125 to acquiring bank 150 associated with provider 130.

Credit card processor gateway 140 may later receive a deposit statementfrom the acquiring bank 150 that allows reconciliation data to be sentto ERP system 155. The reconciliation data may allow ERP system 155 toalert provider 130 if a payment from a purchaser 115 was not completedby the credit card processor 145.

Referring now to FIG. 2A, shown is a block diagram with a detailed viewof subsystems 200 a that may be utilized in association with virtualcard payment receiver 135. Virtual card payment receiver 135 may receiveVCC payments as email 205 a received through the email input 215 a or asa data transfer 210 through the application programming interface (API)input 220. Each input mechanism (email input 215 a and API input 220 mayperform some transformation related to the input type to produce acredit card payment transaction that is stored in secure storage 240.

Still referring to FIG. 2A, the natural language processing (NLP)transformation subsystem 225 may be utilized to process data enteringthe virtual card payment receiver 135 through the email input 215 a. TheNLP transformation subsystem 225 may utilize any combination of applyingtemplates or artificial intelligence (AI) processing to interpret datain email input 215 a that allows the data to be transformed into acredit card payment transaction.

Referring now to FIG. 2B, shown is a block diagram with a detailed viewof subsystems 200 a that may be utilized in association with virtualcard payment receiver 135. Virtual card payment receiver 135 may receiveVCC payments as a file 205 b or an email with one or more attachments205 c. Virtual card payment receiver 135 may detect the file 205 b orthat the email has one or more attachments 205 c. The files 205 b orattachments may be, without limitation, one or more files, one or moreelectronic extensible markup language (XML) files, one or more hypertextmarkup language (HTML) files, one or more object blobs, one or moreportable document format (PDF) files, one or more Excel files, one ormore spreadsheet-type files, one or more comma-separated values (CSV)files, one or more text files, one or more Word files, and/or the like.In some cases, the one or more attachments may be one or more links(e.g., hyperlinks) to one or more attachments or files.

Further, in FIG. 2B, the Virtual card payment receiver 135 may receiveVCC payments as a file 205 b through the file input 215 b or an emailwith one or more attachments 205 c through the email plus attachmentinput 215 c or as a data transfer 210 through the applicationprogramming interface (API) input 220. In some cases, the email plus oneor more attachments 205 c might be analyzed together via the email plusattachment input 215 c. Alternatively, the email plus one or moreattachments 205 c might be analyzed separately via an email input and anattachment input. In other words, the email might be analyzed via anemail input and the one or more attachments might be analyzed via anattachment input. Each input mechanism (file input 205 b, email plusattachment input 215 c, email input, attachment input, and API input220) may perform some transformation related to the input type (e.g.,file, email, attachment, data, etc.) to produce a credit card paymenttransaction that is stored in secure storage 240.

Still referring to FIG. 2B, the natural language processing (NLP)transformation subsystem 225 may be utilized to process data enteringthe virtual card payment receiver 135 through the file input 215 b,through the email plus attachment input 215 c, through the email input,or through the attachment input. The NLP transformation subsystem 225may utilize any combination of applying templates or artificialintelligence (AI) processing to interpret data in the file input 215 b,the email plus attachment input 215 c, the email input, or theattachment input that allows the data to be transformed into a creditcard payment transaction.

Similarly, in FIGS. 2A and 2B, the API data transformation subsystem 230may be utilized to transform data entering the virtual card paymentreceiver 135 through the API input 220. Data entering virtual cardpayment receiver 135 through API input 220 may have any number of datamapping definitions applied to transform the data into a credit cardpayment transaction. The description of the transformation methods inthis example are illustrating the concept of transformation for an inputinto the virtual card payment receiver 135. The example does not intendto limit the number and types of inputs or the transformation methodsthat may be used on any type of input into the virtual card paymentreceiver 135.

Additionally, in FIGS. 2A and 2B, credit card payment transactionsstored in secure storage 240 may be retrieved for processing by creditcard transaction processing subsystem 235 and sent to credit cardprocessor gateway 140. Credit card transaction processing subsystem 235may perform activities such as sending credit card payment transactiondata to credit card processor gateway 140 automatically or manually atthe behest of the provider 130. Provider 130 may utilize the userinterface 245 to configure the virtual card payment receiver 135 withrules that allow the system to determine if a credit card paymenttransaction should be automatically or manually processed. Provider 130may also view credit card payment transactions and instruct the systemto process viewed transactions through the user interface 245. User orInteractive interface 245 represents a user interface such as agraphical user interface (GUI) that may be used by a payment processinganalyst and additionally represents high level artificial intelligence(AI) and machine learning (ML) algorithms that may be invoked to processtransactions that do not initially pass all input validations. Forexample, some transactions may require additional processing to behandled in an automated fashion and for performance or other reasons,additional processing may invoke on an as-needed basis.

Referring now to FIG. 3, shown is a flow diagram depicting theprocessing of a virtual card payment using example method 300. Examplemethod 300 begins at block 305 where VCC payment is received by a systemconfigured in accordance with disclosed techniques via any input methodsupported by an implementation of the system. Flow continues to block310 where it is determined if the virtual card payment may need to beprocessed using natural language processing techniques in accordancewith examples in this disclosure. If natural language processingtechniques are required, flow continues to block 315 through the “YES”prong of the decision diamond block. In block 315, natural languageprocessing techniques may be applied to the virtual card payment data toextract data related to a credit card payment transaction from thevirtual card payment data. The natural language processing techniquesmay include, but are not limited to, using templates or artificialintelligence algorithms to extract data fields. After data is extractedusing the natural language processing techniques, example method 300continues to block 320.

Referring again to decision 310, if the virtual card payment input intothe example system does not require natural language processingtechniques, flow continues to block 320 by following the “NO” prong fromdecision 310. In block 320, virtual card payment data from the virtualcard payment input or data extracted from a virtual card payment inputthat may have required natural language processing may be mapped tocredit card payment transaction data before flow continues to block 325.According to block 325, the credit card payment transaction data may bestored in a secure storage area that may meet strict security guidelinesfor storing sensitive data (e.g. guidelines established by the PaymentCard Industry Data Security Standard (PCI-DSS)). Once the credit cardpayment transaction data is stored in a secure storing area, flowcontinues to block 330 where the credit card payment transaction datamay be retrieved by another subsystem for processing. Flow continues toblock 335 where the credit card payment transaction data may betransferred to a credit card processor gateway for processing the fundstransfer from a purchaser's bank to the provider's bank. Transfer ofdata to the credit card processor's gateway may be subject to rules thatallow the transfer to happen automatically or if the credit card paymenttransaction requires additional processing (up to and including possiblyinteracting with a human) to approve the transfer. Flow continues inparallel to blocks 340 and 345. Block 345 indicates that the credit cardprocessing gateway may update the enterprise resource planning (ERP)system with details about the credit card payment transaction. Theparallel path where flow continues to block 340 may occur some timeafter the credit card payment transaction has been transferred to thecredit card processing gateway. According to the example method 300,this system implementation, in block 340, may receive a depositreconciliation from the provider's bank. Once deposit reconciliation hasbeen received, flow continues to block 350 where the ERP may again beupdated with details about the finalization of the credit card paymenttransaction.

Referring to FIG. 4, shown is an example computing device 400, with ahardware processor 401, and accessible machine-readable instructionsstored on a machine-readable medium 402 that may be used to process aVCC payment, according to one or more disclosed example implementations.FIG. 4 illustrates computing device 400 configured to perform the flowof method 300 as an example. However, computing device 400 may also beconfigured to perform the flow of other methods, techniques, functions,or processes described in this disclosure. In this example of FIG. 4,machine-readable storage medium 402 includes instructions to causehardware processor 401 to perform blocks 305-350 discussed above withreference to FIG. 3.

A machine-readable storage medium, such as 402 of FIG. 4, may includeboth volatile and nonvolatile, removable and non-removable media, andmay be any electronic, magnetic, optical, or other physical storagedevice that contains or stores executable instructions, data structures,program module, or other data accessible to a processor, for examplefirmware, erasable programmable read-only memory (EPROM), random accessmemory (RAM), non-volatile random access memory (NVRAM), optical disk,solid state drive (SSD), flash memory chips, and the like. Themachine-readable storage medium may be a non-transitory storage medium,where the term “non-transitory” does not encompass transitorypropagating signals.

Referring to FIG. 5, shown is a flow diagram depicting an automatedprocess, and possible interactive processing actions with respect toprocessing a VCC payment as an example method 500. According todisclosed techniques, interactive processing actions may be kept to aminimum (and further reduced over time). However, for transitionalimplementation purposes and to process any abnormal events, examplemethod 500 contains an optional path to invoke interactive processing(e.g., with a payment processing employee) in response to such events.Example method 500 begins at block 505 where data for a credit cardpayment transaction is retrieved from secure storage. Flow continues todecision diamond block 510 where the credit card payment transaction isevaluated for automatic processing. For example, a validation may beperformed to determine that all required information is present withinthe transferred information. Additionally, a determination as to a stateof the VCC issuer and user associated with the VCC are still acceptablewith respect to automated VCC processing. In one example, the system maycheck that the VCC issuer is still a viable and trusted entity and thatthe purchaser (e.g., user associated with this VCC transaction)maintains an acceptable relationship with the provider (e.g., contractstill in place, etc.). As illustrated at decision 510, If the instanceof the VCC transaction is approved for automatic processing, the YESprong of decision 510, flow continues to block 515 where the VCC paymenttransaction may be sent (e.g., electronically transferred as a datatransfer, call to API, etc.) to the credit card processing gateway(e.g., credit card processing gateway 140 of FIG. 1).

Still referring to FIG. 5, if the VCC payment transaction may not beautomatically processed based on the evaluation in decision diamondblock 510, flow continues to block 520 through the “NO” prong ofdecision diamond block 510. In block 520, the VCC payment transaction ispresented to an interactive interface, for example, for approval. Theinteractive interface may be implemented in a variety of ways and mayalso be an interface to an escalation system that includes artificialintelligence and machine learning techniques such that an actual humanmay not ultimately be involved. Further, VCC transactions requiringabnormal interactive approval may be grouped and processed as a group byhigher level systems. Each of these concepts is within the scope ofdisclosed techniques to further enhance, improve, and refine VCCtransaction processing.

Continuing with the example method 500, flow continues to block 525where the interactive processing may further review the VCC transactionand optionally provide updated information to allow continued automatedprocessing of the VCC transaction (e.g., approval at block 530).Although not illustrated, exceptions may exist to redirect one or moreVCC transactions for still further review outside the scope of examplemethod 500. The flow of example method 500 culminates at block 515 wherethe VCC payment transaction is sent to the credit card processinggateway (e.g., credit card processing gateway 140 of FIG. 1).

Referring now to FIG. 6, shown is an example computing device 600, witha hardware processor 601, and accessible machine-readable instructionsstored on a machine-readable medium 602 that may be used to executeexample method 500, according to one or more disclosed exampleimplementations. FIG. 6 illustrates computing device 600 configured toperform the flow of method 600 as an example. However, computing device600 may also be configured to perform the flow of other methods,techniques, functions, or processes described in this disclosure. Inthis example of FIG. 6, machine-readable storage medium 602 includesinstructions to cause hardware processor 601 to perform blocks 505-530discussed above with reference to FIG. 5.

A machine-readable storage medium, such as 602 of FIG. 6, may includeboth volatile and nonvolatile, removable and non-removable media, andmay be any electronic, magnetic, optical, or other physical storagedevice that contains or stores executable instructions, data structures,program module, or other data accessible to a processor, for examplefirmware, erasable programmable read-only memory (EPROM), random accessmemory (RAM), non-volatile random access memory (NVRAM), optical disk,solid state drive (SSD), flash memory chips, and the like. Themachine-readable storage medium may be a non-transitory storage medium,where the term “non-transitory” does not encompass transitorypropagating signals.

FIG. 7 represents a computer network infrastructure that may be used toimplement all or part of the disclosed VCC payment processing system,according to one or more disclosed implementations. Networkinfrastructure 700 includes a set of networks where embodiments of thepresent disclosure may operate. Network infrastructure 700 comprises acustomer network 702, network 708, cellular network 703, and a cloudservice provider network 710. In one embodiment, the customer network702 may be a local private network, such as local area network (LAN)that includes a variety of network devices that include, but are notlimited to switches, servers, and routers.

Each of these networks can contain wired or wireless programmabledevices and operate using any number of network protocols (e.g., TCP/IP)and connection technologies (e.g., WiFi® networks, or Bluetooth®. Inanother embodiment, customer network 702 represents an enterprisenetwork that could include or be communicatively coupled to one or morelocal area networks (LANs), virtual networks, data centers and/or otherremote networks (e.g., 708, 710). In the context of the presentdisclosure, customer network 702 may include multiple devices configuredto perform as any subsystem described in the disclosed examples. Also,one of the many computer storage resources in customer network 702 (orother networks shown) may be configured to serve as a computer system toprovide secure storage 240 of FIG. 2.

As shown in FIG. 7, customer network 702 may be connected to one or moreclient devices 704A-E and allow the client devices 704A-E to communicatewith each other and/or with cloud service provider network 710, vianetwork 708 (e.g., Internet). Client devices 704A-E may be computingsystems such as desktop computer 704B, tablet computer 704C, mobilephone 704D, laptop computer (shown as wireless) 704E, and/or other typesof computing systems generically shown as client device 704A.

Network infrastructure 700 may also include other types of devicesgenerally referred to as Internet of Things (IoT) (e.g., edge IOT device705) that may be configured to send and receive information via anetwork to access cloud computing services or interact with a remote webbrowser application (e.g., to receive VCC information).

FIG. 7 also illustrates that customer network 702 includes local computeresources 706A-C that may include a server, access point, router, orother device configured to provide for local computational resourcesand/or facilitate communication amongst networks and devices. Forexample, local compute resources 706A-C may be one or more physicallocal hardware devices, such as the different configurations ofsubsystems outlined above. Local compute resources 706A-C may alsofacilitate communication between other external applications, datasources (e.g., 707A and 707B), and services, and customer network 702.Local compute resource 706C illustrates a possible processing systemcluster with three nodes. Of course, any number of nodes is possible,but three are shown in this example for illustrative purposes.

Network infrastructure 700 also includes cellular network 703 for usewith mobile communication devices. Mobile cellular networks supportmobile phones and many other types of mobile devices such as laptopsetc. Mobile devices in network infrastructure 700 are illustrated asmobile phone 704D, laptop computer 704E, and tablet computer 704C. Amobile device such as mobile phone 704D may interact with one or moremobile provider networks as the mobile device moves, typicallyinteracting with a plurality of mobile network towers 720, 730, and 740for connecting to the cellular network 703.

Although referred to as a cellular network in FIG. 7, a mobile devicemay interact with towers of more than one provider network, as well aswith multiple non-cellular devices such as wireless access points androuters (e.g., local compute resources 706A-C). In addition, the mobiledevices may interact with other mobile devices or with non-mobiledevices such as desktop computer 704B and various types of client device704A for desired services. Although not specifically illustrated in FIG.7, customer network 702 may also include a dedicated network device(e.g., gateway or router) or a combination of network devices (notshown) that implement a customer firewall or intrusion protectionsystem.

FIG. 7 illustrates that customer network 702 is coupled to a network708. Network 708 may include one or more computing networks availabletoday, such as other LANs, wide area networks (WAN), the Internet,and/or other remote networks, in order to transfer data between clientdevices 704A-D and cloud service provider network 710. Each of thecomputing networks within network 708 may contain wired and/or wirelessprogrammable devices that operate in the electrical and/or opticaldomain.

In FIG. 7, cloud service provider network 710 is illustrated as a remotenetwork (e.g., a cloud network) that is able to communicate with clientdevices 704A-E via customer network 702 and network 708. The cloudservice provider network 710 acts as a platform that provides additionalcomputing resources to the client devices 704A-E and/or customer network702. In one embodiment, cloud service provider network 710 includes oneor more data centers 712 with one or more server instances 714.

FIG. 8 illustrates a computer processing device 800 that may be used toimplement the functions, modules, processing platforms, executionplatforms, communication devices, and other methods and processes ofthis disclosure. For example, computing device 800 illustrated in FIG. 8could represent a client device or a physical server device and includeeither hardware or virtual processor(s) depending on the level ofabstraction of the computing device. In some instances (withoutabstraction), computing device 800 and its elements, as shown in FIG. 8,each relate to physical hardware. Alternatively, in some instances one,more, or all of the elements could be implemented using emulators orvirtual machines as levels of abstraction. In any case, no matter howmany levels of abstraction away from the physical hardware, computingdevice 800 at its lowest level may be implemented on physical hardware.

As also shown in FIG. 8, computing device 800 may include one or moreinput devices 830, such as a keyboard, mouse, touchpad, or sensorreadout (e.g., biometric scanner) and one or more output devices 815,such as displays, speakers for audio, or printers. Some devices may beconfigured as input/output devices also (e.g., a network interface ortouchscreen display).

Computing device 800 may also include communications interfaces 825,such as a network communication unit that could include a wiredcommunication component and/or a wireless communications component,which may be communicatively coupled to processor 805. The networkcommunication unit may utilize any of a variety of proprietary orstandardized network protocols, such as Ethernet, TCP/IP, to name a fewof many protocols, to effect communications between devices. Networkcommunication units may also comprise one or more transceiver(s) thatutilize the Ethernet, power line communication (PLC), WiFi, cellular,and/or other communication methods.

As illustrated in FIG. 8, computing device 800 includes a processingelement such as processor 805 that contains one or more hardwareprocessors, where each hardware processor may have a single or multipleprocessor cores. In one embodiment, the processor 805 may include atleast one shared cache that stores data (e.g., computing instructions)that are utilized by one or more other components of processor 805. Forexample, the shared cache may be a locally cached data stored in amemory for faster access by components of the processing elements thatmake up processor 805. In one or more embodiments, the shared cache mayinclude one or more mid-level caches, such as level 2 (L2), level 3(L3), level 4 (L4), or other levels of cache, a last level cache (LLC),or combinations thereof. Examples of processors include but are notlimited to a central processing unit (CPU) a microprocessor. Althoughnot illustrated in FIG. 8, the processing elements that make upprocessor 805 may also include one or more of other types of hardwareprocessing components, such as graphics processing units (GPU),application specific integrated circuits (ASICs), field-programmablegate arrays (FPGAs), and/or digital signal processors (DSPs).

FIG. 8 illustrates that memory 810 may be operatively andcommunicatively coupled to processor 805. Memory 810 may be anon-transitory medium configured to store various types of data. Forexample, memory 810 may include one or more storage devices 820 thatcomprise a non-volatile storage device and/or volatile memory. Volatilememory, such as random-access memory (RAM), can be any suitablenon-permanent storage device. The non-volatile storage devices 820 caninclude one or more disk drives, optical drives, solid-state drives(SSDs), tap drives, flash memory, read only memory (ROM), and/or anyother type of memory designed to maintain data for a duration of timeafter a power loss or shut down operation. In certain instances, thenon-volatile storage devices 820 may be used to store overflow data ifallocated RAM is not large enough to hold all working data. Thenon-volatile storage devices 820 may also be used to store programs thatare loaded into the RAM when such programs are selected for execution.

Persons of ordinary skill in the art are aware that software programsmay be developed, encoded, and compiled in a variety of computinglanguages for a variety of software platforms and/or operating systemsand subsequently loaded and executed by processor 805. In oneembodiment, the compiling process of the software program may transformprogram code written in a programming language to another computerlanguage such that the processor 805 is able to execute the programmingcode. For example, the compiling process of the software program maygenerate an executable program that provides encoded instructions (e.g.,machine code instructions) for processor 805 to accomplish specific,non-generic, particular computing functions.

After the compiling process, the encoded instructions may then be loadedas computer executable instructions or process steps to processor 805from storage device 820, from memory 810, and/or embedded withinprocessor 805 (e.g., via a cache or on-board ROM). Processor 805 may beconfigured to execute the stored instructions or process steps in orderto perform instructions or process steps to transform the computingdevice into a non-generic, particular, specially programmed machine orapparatus. Stored data, e.g., data stored by a storage device 820, maybe accessed by processor 805 during the execution of computer executableinstructions or process steps to instruct one or more components withinthe computing device 800.

A user interface (e.g., output devices 815 and input devices 830) caninclude a display, positional input device (such as a mouse, touchpad,touchscreen, or the like), keyboard, or other forms of user input andoutput devices. The user interface components may be communicativelycoupled to processor 805. When the output device is or includes adisplay, the display can be implemented in various ways, including by aliquid crystal display (LCD) or a cathode-ray tube (CRT) or lightemitting diode (LED) display, such as an organic light emitting diode(OLED) display. Persons of ordinary skill in the art are aware that thecomputing device 800 may comprise other components well known in theart, such as sensors, powers sources, and/or analog-to-digitalconverters, not explicitly shown in FIG. 8.

Referring now to FIG. 9, shown is a credit card processing ecosystem 900where a cardholder 905 establishes a relationship with a card issuer 910to receive either a physical credit card or VCC as indicated by creditcard 915. In this example, credit card 915 may be used for performingcredit card payments to a provider 925. Cardholder 905, in this context,represents any entity that can be held responsible for paymenttransactions against an account ledger held by card issuer 910. A commonexample would be any person that may have one or more credit cards forpurposes of making purchases at physical retail locations, onlineecommerce merchants, or any other establishment that accepts creditcards as payment. The cardholder 905 may also be a goods or serviceprovider or any other entity with which card issuer 910 may establish afinancial relationship.

Card issuer 910, in the context of this example, represents a businessthat issues credit card 915 with an identifying number that the cardissuer 910 associates with an account ledger tracking credits and debitsto the account by cardholder 905. A common example of card issuer 910 isa bank that establishes a line of credit that is used to fundtransactions made by cardholder 905 with credit card 915. Card issuer910 may not be limited to banking institutions and the types of accountsassociated with credit card 915 are not limited to lines of credit. Cardissuer 910, for example, may associate cardholder 905 with a checkingaccount as the account that funds purchases made with credit card 915. Acard issued with a checking account as the method of funding purchasesis commonly known as a “debit card” and will often serve the purpose ofcredit card 915 as well has have the capability to allow the cardholder905 to interact with the card issuer's 910 Automated Teller Machines(ATM) to withdraw cash from an account associated with cardholder 905.

Card issuer 910 may also associate credit card 915 with an accountledger that is not associated with a specific cardholder 905. Oneexample of this practice may be observed with a “stored value card” or“cash card” that is commonly purchased at a retail location as a creditcard funded by a cash deposit made at the time of purchase. The “storedvalue card” or “cash card” may function as credit card 915 that may beaccepted by any merchant 925 that accepts credit card payments. Avariation of the “stored value card” may be observed when provider 925acts as card issuer 910 to issue a “gift card” that may only be used forpurchases from provider 925.

Many different techniques may be used by card issuer 910 to associatecredit card 915 with an account ledger and corresponding cardholder 905.One example association of a variation includes the “stored value card”where a cash account may be associated with credit card 915 andcardholder 905 as a method cardholder 905 receiving payments from anemployer to transfer wages to cardholder 905. This concept is commonlyreferred to as a “payroll card” where the employer establishes arelationship with card issuer 910 to generate a “stored value card”credit card as an example of credit card 915 further associated withcardholder 905. Card issuer 910 may issue a physical credit card 915 tocardholder 905 with an account number that allows cardholder 905 to makepurchases with any provider 925 that accepts credit cards. Credit card915 held by cardholder 905 may further allow for cash withdrawals viaATM transactions as well as credit card purchases. Card issuer 910, inthis case, may issue the employer of cardholder 905 a separate accountnumber tied to the account ledger of credit card 915 that allows theemployer to credit or debit the account through a funds transfer made atthe time the employer processes the payroll payments for cardholder 905.

One example of credit card 915 given to cardholder 905 by card issuer910 is a physical card with a number imprinted on one of the card'ssurfaces. The number imprinted on credit card 915, in this example, iscommonly referred to the “payment card number”, “primary account number(PAN),” or simply as the “card number.” The card number may be a numbergenerated in accordance with the ISO/IEC 7812 standard and may beencoded to identify, for example, the issuer of the card, the primarypurpose of the card, and an identifier that allows card issuer 910 toassociate credit card 915 with an account ledger assigned to cardholder905. The card number may be validated as a valid card number followingthe ISO/IEC 7812 standard using a validation algorithm such as the LehnAlgorithm. Card number validation, in this context, allows a provider925 to prevent fees related to processing a credit card payment if acard number fails to validate using the Luhn Algorithm.

Credit card 915 may have a number of tangible and non-tangible forms.The example of a physical card described above represents a commonexample of a tangible instance of credit card 915. Other examples of atangible instance of credit card 915 may include issuing a token that isstored in a smart phone owned by cardholder 905. This token may becommunicated to a provider 925 at the time of payment. In this context,the token may be an alpha-numeric value that may be linked to creditcard 915 issued to cardholder 905. The token often may be generated inconjunction with a security mechanism to prevent storage of the linkednumber of credit card 915 in a potentially unsecure device. Provider925, in this example, may have software compatible with receiving andtranslating the token from the smart phone to process a payment to thelinked credit card 915 when cardholder 905 initiates a transmission ofthe token from the phone to provider 925 at the time of purchase. Thereare many methods to create a tangible representation of credit card 915.

In contrast to a physical credit card, a VCC is an example of anon-tangible form of credit card 915. The VCC may be generated by cardissuer 910 as a non-tangible credit card with a card number that followsthe ISO/IEC 7812 standard, may validate as a valid credit card using theLuhn Algorithm, and may be accepted for payment as a credit card 915 bya provider 925 that accepts credit card payments. A VCC, however, may beissued using a card number communicated electronically or verbally tocardholder 905 rather than as a tangible credit card as described in theprevious example. Cardholder 905 may in turn communicate the VCC numberto provider 925 electronically or verbally during a purchase made usingthe VCC example of credit card 915.

Card issuer 910 may issue tangible or non-tangible credit cards 915 thatmay function as a credit card 915 with a restricted scope of use. Insome examples, card issuer 910 may issue credit card 915 in tangible ornon-tangible form with a restricted scope of usage at the request ofcardholder 905. The restricted scope may include limiting purchases tobe processed by a specific provider 925, limiting the amount that may beused for a purchase, or limiting the time period in which credit card915 may be used for purchases. The types of limitations that may beplaced on each credit card 915 issued for restricted scope of use isunlimited.

When cardholder 905 makes a purchase from provider 925 using credit card915, provider 925, in general, has a card acceptance system 920 that maybe used to identify the account number of credit card 915 and associatecredit card 915 with a purchase. A simple example of a card acceptancesystem 920 may be a physical device that reads a physical instance ofcredit card 915 in the presence of both cardholder 905 and provider 925.A card acceptance system 920 may allow the acceptance of credit card 915in both tangible and non-tangible forms. Shopping web sites, automatedphone attendant systems, virtual terminals, or any other system thatrecords the account number of credit card 915 and associates the numberwith a financial transaction.

A financial transaction between cardholder 905 and provider 925 usingcredit card 915 may associate varying amounts of metadata with thefinancial transaction. A financial transaction, in this context, refersto an action of provider 925 recording transfer of goods or services tocardholder 905 using credit card 915 as a payment method. Most financialtransactions involving credit card 915, for example, associate metadatasuch as a monetary amount with the financial transaction. The financialtransaction and some portion of the associated data may then betransmitted directly to a credit card processor 930 or indirectly to acredit card processor 930 through a credit card processor gateway 945 aspart of a credit card transaction. A credit card transaction, in thiscontext, refers to the process where a credit card processor 930facilitates the transfer of money from the issuing institution forcardholder 905 (e.g., the card issuer 910) to a bank of provider 925(e.g., transaction acquirer 935).

While provider 925 may associate different metadata with a financialtransaction, not all of the metadata may be transmitted to credit cardprocessor 930 as part of processing the financial transaction. Creditcard 915 may have been created by card issuer 910 with a specialcategory that limits the type of metadata that credit card processor 930is expected to accept. Credit card 915 with a Level 1 categorydesignation, for example, may be considered a “B2C” card where theminimum metadata required for processing a credit card transaction mayinclude account number for credit card 915 and the amount of thetransaction. Credit card 915 with a Level 2 category designation, forexample, may also be considered a “B2B” card. A Level 2 credit cardtransaction may allow all metadata allowed by a Level 1 card butadditionally allow data such as a tax amount included in the credit cardtransaction amount, a customer's purchase order number, or other datathat may assist a business in tracking payments made by business creditcards. Still further, credit card 915 with a Level 3 categorydesignation, for example, may also be considered a “B2B” card. A Level 3credit card transaction may allow all metadata allowed by Level 1 andLevel 2 transactions but additionally allow metadata observed in invoiceline item details. Invoice line item details may include a line itemdescription, quantity, price per unit, unit of measure, extended price,and any other metadata supported by credit card processor 930 for Level3 transactions.

Provider 925 processes a credit card transaction, for example, when cardacceptance system 920 associates credit card 915 with a financialtransaction. Card acceptance system 920 may transmit the credit cardtransaction data directly to credit card processor 930 or indirectly tocredit card processor 930 through credit card processor gateway 945.Credit card processor 930 may thus facilitate transfer of money fromcard issuer 910 on behalf of cardholder 905 and transaction acquirer 935on behalf of provider 925 through interchange network 950 associatedwith credit card processor 930. Credit card processor 930, in thiscontext, refers to an entity such as Visa, Mastercard, American Express,or other card processors that establish an interchange network 950 tofacilitate the transfer of money between card issuer 910 and transactionacquirer 935.

Card acceptance system 920 may communicate credit card transactionsdirectly to credit card processor 930. Transmitting a credit cardtransaction directly to credit card processor 930 may limit the types ofcards provider 925 may accept to cards associated with the branding ofan instance of credit card processor 930. Credit card processor 930 thatis associated with Visa, for example, may not accept Mastercardtransactions. Provider 925 may instead use a credit card processorgateway 945 system that may aggregate the capability of multiple creditcard processors 930 as a single point where credit card transactions maybe sent for processing. Credit card processor gateway 945 may becomposed of several layers of credit card processor gateways 945, eachlayer adding a functionality for provider 925 that may be utilized tomaximize the financial benefit of accepting credit card payments. Creditcard processor gateway 945 may, for example, provide services such asfraud prevention checks on each credit card transaction before passingthe transaction to credit card processor 930. In another example, as anaggregator of credit card processors 930, a credit card processorgateway 945 may add “credit card processor routing” capabilities thatallow provider 925 to process a credit card transaction while minimizingthe fees paid for use of credit card processor 930 (e.g., fee forprocessing the credit card transaction). One example of credit cardprocessor routing may be observed when credit card 915 may be used in acredit card transaction that is detected as a Level 3 American Expresscard. In this example, credit card processor gateway 945 mayautomatically associate Level 3 metadata with the transaction and routethe transaction to utilize a merchant account configuration with creditcard processor 930 that discounts the transaction fees for credit cardtransactions that have a higher degree of confidence that the cardholder905 presenting the Level 3 credit card 915 is making a purchase that hasa low probability of being disputed or discovered as fraudulent.

Credit card processor gateway 945 may also add value by updating anEnterprise Resource Planning System (ERP) 940 associated with provider925. The update may include update to accounts receivable data for eachcredit card transaction processed. Interfacing with Enterprise ResourcePlanning System 940 may allow provider 925 to reconcile deposits made toa bank (transaction acquirer 935) associated with provider 925 by creditcard processors 930 through interchange network 950. Credit cardprocessor gateway 945 may additionally update the accounts receivableledger of the Enterprise Resource Planning System 940 with transactionamounts of each credit card transaction. The accounts receivable ledgermay then be reconciled with deposit statements provided to provider 925by transaction acquirer 935. In some cases, Credit card processorgateway 945 may receive multiple deposit statements from multipletransaction acquirers 935 to facilitate the reconciliation.Reconciliation may allow the merchant 925 to detect when a cardholder905 created a dispute with card issuer 910, thereby causing card issuer910 to request credit card processor 930 to reverse the transfer offunds from the account associated with cardholder 905 to an account forprovider 925. Many additional services or features may be provided bycredit card processor gateway 945.

In the above discussion of example credit card processing ecosystem 900,the concept of “transmitting”, “transferring”, and “communicating” theaccount number of a credit card 915 refers to any method of exchangingdata that may include the account number between one entity and another.A cardholder 905, for example, providing credit card 915 to cardacceptance system 920 may be simply the act of cardholder 905 passing atangible instance of credit card 915 to provider 925. Provider 925 maythen swipe credit card 915 through a magnetic stripe reader attached tocard acceptance system 920.

Exchange of data in credit card processing ecosystem 900 may commonlyoccur between entities in electronic form. An exchange betweencardholder 905 and card acceptance system 920, for example, may be doneby cardholder 905 submitting the account number of credit card 915 in ashopping cart created by provider 925. An exchange of data between cardacceptance system 920 and credit card processor gateway 945 may, forexample, be completely automated by taking financial transaction datafrom credit card acceptance system 920, transforming it from a financialtransaction to an electronic payload representing a credit cardtransaction, and transmitting the credit card transaction payload tocredit card processor gateway 945.

Electronic data transfer, in this context, refers to any transmissionbetween two entities. Electronic data transfer between two entities maybe facilitated by a variety of communication mediums such as local orwide area networks, cellular networks, or any other communication mediumfacilitating communication between two entities. The transport protocolsused to transmit the electronic data over the communication medium arevast and any form of electronic data transfer may be used for disclosedimplementations. Some examples of the transport protocol used totransmit electronic data may include Transport Control Protocol/InternetProtocol (TCP/IP), Email, File Transport Protocol (FTP) and securevariants of FTP, Hypertext Transfer Protocol (HTTP) and secure variantsof HTTP, or any other protocol that facilities the transport ofelectronic data in any encoded or unencoded form.

The electronic data may be in any form required to represent a creditcard transaction. In a simple example, the electronic data representingthe credit card transaction may be in a text representation of a spokenlanguage such as might be observed with an email exchange. Electronicdata for machine-to-machine transfer may utilize forms such asElectronic Data Interchange (EDI), Extensible Markup Language (XML),Simple Object Access Protocol (SOAP), JavaScript Object Notation (JSON),or any other form that allows for efficient transfer of electronic databetween machines.

The transfer of data may be classified as real-time data exchange orbatch data exchange. In this context, a real-time data exchange may beutilized to transfer data for a single credit card transaction for thepurpose of receiving an immediate response from the receiver of theelectronic data related to the status of processing the credit cardtransaction. A real-time data exchange may be utilized, for example, toverify the availability of funds to cover a purchase using credit card915. A batch data exchange, in this context, refers to the transfer ofdata related to one or more credit card transaction that may receive adelayed response related to the status of the credit card transactionsin the transmitted batch. An example of a batch data exchange may bewhen the credit card transactions processed for any given period of timeare transmitted in a logical grouping (such as a file) to a credit cardprocessor 930 as an instruction to the credit card processor 930 tobegin transferring funds between the card issuer 910 and the transactionacquirer 935. The number of credit card transactions in the batch mayrequire a period of time to process and therefore a response indicatingthe processing status may not be available until all the credit cardtransactions in the batch have been processed.

Certain terms have been used throughout this description and claims torefer to particular system components. As one skilled in the art willappreciate, different parties may refer to a component by differentnames. This document does not intend to distinguish between componentsthat differ in name but not function. In this disclosure and claims, theterms “including” and “comprising” are used in an open-ended fashion,and thus should be interpreted to mean “including, but not limited to .. . .” Also, the term “couple” or “couples” is intended to mean eitheran indirect or direct wired or wireless connection. Thus, if a firstdevice couples to a second device, that connection may be through adirect connection or through an indirect connection via other devicesand connections. The recitation “based on” is intended to mean “based atleast in part on.” Therefore, if X is based on Y, X may be a function ofY and any number of other factors.

The above discussion is meant to be illustrative of the principles andvarious implementations of the present disclosure. Numerous variationsand modifications will become apparent to those skilled in the art oncethe above disclosure is fully appreciated. It is intended that thefollowing claims be interpreted to embrace all such variations andmodifications.

What is claimed is:
 1. A computer system comprising: one or moreprocessors; a memory communicatively coupled to the one or moreprocessors and storing instructions executable by the one or moreprocessors to cause the computer system to provide a dual input virtualcredit card (VCC) payment receiver function implemented on the computersystem to: provide a first input, as an authenticated input, to receiveinformation from a previously authenticated known first entity; providea second input to receive information from a previously unauthenticatedand not yet identified second entity; responsive to receipt of firstdigital information at an application program interface (API) associatedwith the first input: determine that the first digital information isrepresentative of a first VCC transaction; perform API datatransformation and data mapping to process the first digital informationwith respect to payment processing for the first VCC transaction; andprovide the first VCC transaction to a secure storage for processing bya credit card transaction processing system of the computer system, thefirst VCC transaction identifying a receiving account and a paymentaccount; responsive to receipt of second digital information via thesecond input: determine that the second digital information isrepresentative of a second VCC transaction, the second digitalinformation received as a digital message via an electronic datatransfer at the second input, the digital message including metadatarelating to a transaction between a provider and a purchaser, themetadata further including remittance information for the transactionidentifying a remittance from the purchaser to the provider, wherein thedigital message is an email message; perform natural language processing(NLP) on first data of the email message to identify the metadata andignore additional extraneous information; parse the metadata of thedigital message to identify the second entity as an authenticated senderof the second VCC transaction; parse the metadata to identify attributesto exchange with a first account associated with the provider and asecond account associated with the purchaser; based on the identifiedattributes to exchange with the first account associated with theprovider and the second account associated with the purchaser, determinethat the identified attributes are sufficient to perform the second VCCtransaction; based on the determination that the identified attributesare sufficient to perform the second VCC transaction, transform theidentified attributes into a standard form acceptable by the credit cardtransaction processing system; and provide the second VCC transactionincluding the identified attributes transformed into the standard formto the secure storage for processing by the credit card transactionprocessing system; and initiate transmission, from the credit cardtransaction processing system to a financial institution, of informationto complete payment processing for the first VCC transaction and thesecond VCC transaction, wherein the credit card transaction processingsystem is unaware of whether the transaction was initiated using thefirst input or the second input.
 2. The computer system of claim 1,wherein the digital message further comprises at least one of seconddata transmitted as an electronic extensible markup language (XML) file,third data transmitted as a hypertext markup language (HTML) file,fourth data transmitted as a portable document format (PDF) file, fifthdata transmitted as an Excel file, sixth data transmitted as aspreadsheet-type file, seventh data transmitted as comma-separatedvalues (CSV) file, eighth data transmitted as a text file, ninth datatransmitted as a Word file, tenth data transmitted as a file, oreleventh data transmitted as an object blob.
 3. The computer system ofclaim 2, wherein the instructions further include instructions to causethe computer system to: perform NLP on at least one of the second datatransmitted as the electronic extensible markup language (XML) file, thethird data transmitted as the hypertext markup language (HTML) file, thefourth data transmitted as the portable document format (PDF) file, thefifth data transmitted as the Excel file, the sixth data transmitted asthe spreadsheet-type file, the seventh data transmitted ascomma-separated values (CSV) file, the eighth data transmitted as thetext file, the ninth data transmitted as the Word file, the tenth datatransmitted as the file, or the eleventh data transmitted as the objectblob to identify second metadata and ignore additional second extraneousinformation; and parse the second metadata to identify one or moresecond attributes to exchange with the first account associated with theprovider and the second account associated with the purchaser; based onthe identified second attributes to exchange with the first accountassociated with the provider and the second account associated with thepurchaser, determine that the identified second attributes aresufficient to supplement the second VCC transaction or perform a thirdVCC transaction; based on the determination that the identified secondattributes are sufficient to supplement the second VCC transaction orperform a third VCC transaction, transform the identified secondattributes into the standard form acceptable by the credit cardtransaction processing system; and provide the second VCC transaction orthe third VCC transaction including the identified second attributestransformed into the standard form to the secure storage for processingby the credit card transaction processing system.
 4. The computer systemof claim 1, wherein the instructions further cause the computer systemto: perform validation of the second entity using an emailauthentication protocol.
 5. The computer system of claim 1, wherein theinstructions further include instructions to cause the computer systemto: perform machine learning analysis of the metadata identified by theNLP to create a credit card transaction instance representative of thetransaction.
 6. The computer system of claim 5, wherein the instructionsfurther include instructions to cause the computer system to: interfacewith a credit card processor as a gateway for multiple instances ofcredit card transactions including the transaction.
 7. The computersystem of claim 1, wherein the instructions further include instructionsto cause the computer system to: perform an update to an enterpriseresource planning (ERP) system associated with the provider to reflectprovider system information representative of the transaction.
 8. Thecomputer system of claim 7, wherein the instructions further includeinstructions to cause the computer system to: perform an update toinventory data contained in the ERP system representative of thetransaction.
 9. A computer-implemented method comprising: providing adual input virtual credit card (VCC) payment receiver functionimplemented on a computer system, the dual input VCC payment receiverfunction to: provide a first input, as an authenticated input, toreceive information from a previously authenticated known first entity;provide a second input to receive information from a previouslyunauthenticated and not yet identified second entity; responsive toreceipt of first digital information at an application program interface(API) associated with the first input: determine that the first digitalinformation is representative of a first VCC transaction; perform APIdata transformation and data mapping to process the first digitalinformation with respect to payment processing for the first VCCtransaction; and provide the first VCC transaction to a secure storagefor processing by a credit card transaction processing system of thecomputer system, the first VCC transaction identifying a receivingaccount and a payment account; responsive to receipt of second digitalinformation via the second input: determine that the second digitalinformation is representative of a second VCC transaction, the seconddigital information received as a digital message via an electronic datatransfer at the second input, the digital message including metadatarelating to a transaction between a provider and a purchaser, themetadata further including remittance information for the transactionidentifying a remittance from the purchaser to the provider, wherein thedigital message is an email message; perform natural language processing(NLP) on first data of the email message to identify the metadata andignore additional extraneous information; parse the metadata of thedigital message to identify the second entity as an authenticated senderof the second VCC transaction; parse the metadata to identify attributesto exchange with a first account associated with the provider and asecond account associated with the purchaser; based on the identifiedattributes to exchange with the first account associated with theprovider and the second account associated with the purchaser, determinethat the identified attributes are sufficient to perform the second VCCtransaction; based on the determination that the identified attributesare sufficient to perform the second VCC transaction, transform theidentified attributes into a standard form acceptable by the credit cardtransaction processing system; and provide the second VCC transactionincluding the identified attributes transformed into the standard formto the secure storage for processing by the credit card transactionprocessing system; and initiate transmission, from the credit cardtransaction processing system to a financial institution, of informationto complete payment processing for the first VCC transaction and thesecond VCC transaction, wherein the credit card transaction processingsystem is unaware of whether the transaction was initiated using thefirst input or the second input.
 10. The computer-implemented method ofclaim 9, wherein the digital message further comprises at least one ofsecond data transmitted as an electronic extensible markup language(XML) file, third data transmitted as a hypertext markup language (HTML)file, fourth data transmitted as a portable document format (PDF) file,fifth data transmitted as an Excel file, sixth data transmitted as aspreadsheet-type file, seventh data transmitted as comma-separatedvalues (CSV) file, eighth data transmitted as a text file, ninth datatransmitted as a Word file, tenth data transmitted as a file, oreleventh data transmitted as an object blob.
 11. Thecomputer-implemented method of claim 9, further comprising: performingvalidation of the second entity using an email authentication protocol.12. The computer-implemented method of claim 9, wherein the methodfurther comprises: performing machine learning analysis of the metadataidentified by the NLP to create a credit card transaction instancerepresentative of the transaction.
 13. The computer-implemented methodof claim 9, further comprising: performing machine learning analysis ofthe metadata within the digital message to: create a credit cardtransaction instance representative of the transaction.
 14. Anon-transitory computer readable medium comprising computer executableinstructions that, when executed by one or more processing units, causethe one or more processing units to: provide a dual input virtual creditcard (VCC) payment receiver function implemented on a computer system,the dual input VCC payment receiver function to: provide a first input,as an authenticated input, to receive information from a previouslyauthenticated known first entity; provide a second input to receiveinformation from a previously unauthenticated and not yet identifiedsecond entity; responsive to receipt of first digital information at anapplication program interface (API) associated with the first input:determine that the first digital information is representative of afirst VCC transaction; perform API data transformation and data mappingto process the first digital information with respect to paymentprocessing for the first VCC transaction; and provide the first VCCtransaction to a secure storage for processing by a credit cardtransaction processing system of the computer system, the first VCCtransaction identifying a receiving account and a payment account;responsive to receipt of second digital information via the secondinput: determine that the second digital information is representativeof a second VCC transaction, the second digital information received asa digital message via an electronic data transfer at the second input,the digital message including metadata relating to a transaction betweena provider and a purchaser, the metadata further including remittanceinformation for the transaction identifying a remittance from thepurchaser to the provider, wherein the digital message is an emailmessage; perform natural language processing (NLP) on first data of theemail message to identify the metadata and ignore additional extraneousinformation; parse the metadata of the digital message to identify thesecond entity as an authenticated sender of the second VCC transaction;parse the metadata to identify attributes to exchange with a firstaccount associated with the provider and a second account associatedwith the purchaser; based on the identified attributes to exchange withthe first account associated with the provider and the second accountassociated with the purchaser, determine that the identified attributesare sufficient to perform the second VCC transaction; based on thedetermination that the identified attributes are sufficient to performthe second VCC transaction, transform the identified attributes into astandard form acceptable by the credit card transaction processingsystem; and provide the second VCC transaction including the identifiedattributes transformed into the standard form to the secure storage forprocessing by the credit card transaction processing system; andinitiate transmission, from the credit card transaction processingsystem to a financial institution, of information to complete paymentprocessing for the first VCC transaction and the second VCC transaction,wherein the credit card transaction processing system is unaware ofwhether the transaction was initiated using the first input or thesecond input.
 15. The non-transitory computer readable medium of claim14, wherein the digital message further comprises at least one of seconddata transmitted as an electronic extensible markup language (XML) file,third data transmitted as a hypertext markup language (HTML) file,fourth data transmitted as a portable document format (PDF) file, fifthdata transmitted as an Excel file, sixth data transmitted as aspreadsheet-type file, seventh data transmitted as comma-separatedvalues (CSV) file, eighth data transmitted as a text file, ninth datatransmitted as a Word file, tenth data transmitted as a file, oreleventh data transmitted as an object blob.
 16. The non-transitorycomputer readable medium of claim 14, wherein the instructions furtherinclude instructions to cause the one or more processing units to:perform validation of the second entity using an email authenticationprotocol.
 17. The non-transitory computer readable medium of claim 14,wherein the instructions further include instructions to cause the oneor more processing units to: perform machine learning analysis of themetadata identified by the NLP to create a credit card transactioninstance representative of the transaction.
 18. The computer system ofclaim 14, wherein the instructions further include instructions to causethe one or more processing units to: perform machine learning analysisof the metadata within the digital message to create a credit cardtransaction instance representative of the transaction.
 19. The computersystem of claim 18, wherein the instructions further includeinstructions to cause the one or more processing units to: interfacewith a credit card processor as a gateway for multiple instances ofcredit card transactions including the transaction.
 20. The computersystem of claim 14, wherein the instructions further includeinstructions to cause the one or more processing units to: perform anupdate to an enterprise resource planning (ERP) system associated withthe provider to reflect provider system information representative ofthe transaction.